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      Identifying ChIP-seq enrichment using MACS.

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          Abstract

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.

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          Author and article information

          Journal
          Nat Protoc
          Nature protocols
          Springer Science and Business Media LLC
          1750-2799
          1750-2799
          Sep 2012
          : 7
          : 9
          Affiliations
          [1 ] Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai, China.
          Article
          nprot.2012.101 NIHMS505156
          10.1038/nprot.2012.101
          3868217
          22936215
          73fdcd03-9a04-403a-a50b-4745bc72f4a8
          History

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